Quantum Principal Component Analysis
Quantum Principal Component Analysis is a quantum algorithm that extends the classical principal component analysis by leveraging quantum superposition and entanglement to exponentially accelerate the extraction of principal components from high-dimensional data encoded in quantum states.
31
Publications
3.8K
Citations
119
Authors
75
Institutions
Publications per year
2017–2026
24
31
Quantum principal component analysis
Seth Lloyd, Masoud Mohseni, Patrick Rebentrost · Nature Physics · 2014 · 1.4K citations · Full text
Quantum advantage in learning from experiments
Hsin-Yuan Huang, Michael Broughton, Jordan Cotler et al. · Science · 2022 · 508 citations · Full text
Computing, Computer Science, Physics +13
Variational quantum state diagonalization
Ryan LaRose, Arkin Tikku, Étude O’Neel-Judy et al. · npj Quantum Information · 2019 · 206 citations · Full text
Computing, Computer Science, Physics +12
1–5 of 31
119
5
h-index
Massachusetts Institute of Technology, United States
3 publications · 1.4K citations
3
h-index
3
h-index
2
h-index
2
h-index
1–5 of 119
75
National University of Singapore
Singapore, Singapore
3 h-index
3 publications
152 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
5 publications
2.9K citations

Universidad de Sevilla
Seville, Spain
2 h-index
2 publications
84 citations
Multiverse Computing (Spain)
San Sebastian, Spain
2 h-index
2 publications
84 citations
IQM (Germany)
Munich, Germany
2 h-index
4 publications
168 citations
Xanadu Quantum Technologies (Canada)
Toronto, Canada
2 h-index
3 publications
157 citations
University of Oklahoma
Norman, United States
2 h-index
5 publications
167 citations
Centre for Quantum Technologies
Singapore, Singapore
2 h-index
2 publications
141 citations
1–8 of 75
Repository · 4 publications · 184 citations
4
h-index
2 publications · 94 citations
2
h-index
2 publications · 63 citations
2
h-index
PRL · 2 publications · 201 citations
2
h-index
1 publications · 206 citations
1
h-index
1–5